Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA.
Mem Cognit. 2012 Nov;40(8):1352-65. doi: 10.3758/s13421-012-0227-z.
Complex problem solving in naturalistic environments is fraught with uncertainty, which has significant impacts on problem-solving behavior. Thus, theories of human problem solving should include accounts of the cognitive strategies people bring to bear to deal with uncertainty during problem solving. In this article, we present evidence that analogy is one such strategy. Using statistical analyses of the temporal dynamics between analogy and expressed uncertainty in the naturalistic problem-solving conversations among scientists on the Mars Rover Mission, we show that spikes in expressed uncertainty reliably predict analogy use (Study 1) and that expressed uncertainty reduces to baseline levels following analogy use (Study 2). In addition, in Study 3, we show with qualitative analyses that this relationship between uncertainty and analogy is not due to miscommunication-related uncertainty but, rather, is primarily concentrated on substantive problem-solving issues. Finally, we discuss a hypothesis about how analogy might serve as an uncertainty reduction strategy in naturalistic complex problem solving.
在自然环境中解决复杂问题充满了不确定性，这对问题解决行为有重大影响。因此，人类问题解决理论应该包括人们在解决问题时应对不确定性的认知策略。在本文中，我们提出了类比是这样一种策略的证据。通过对火星探测器任务中科学家自然主义问题解决对话中类比和表达不确定性之间的时间动态进行统计分析，我们表明表达的不确定性的峰值可靠地预测了类比的使用（研究 1），并且在使用类比后，表达的不确定性会降低到基线水平（研究 2）。此外，在研究 3 中，我们通过定性分析表明，不确定性和类比之间的这种关系不是由于与误解相关的不确定性，而是主要集中在实质性的问题解决问题上。最后，我们讨论了一个假设，即类比如何在自然主义的复杂问题解决中作为一种减少不确定性的策略。
